Effect of Multimedia Instructional Strategy on Students’ Academic Achievement in Mechanical Trades in Technical Colleges

Abstract

Modeling cognitive processes in clinical learning environments is a necessary first step towards improving learning assessment and medical practice by using an alternative assessment model. Verbal protocol and cognitive content analyses are effective methods of exploring such cognitive processes. For the purpose of simplifying the discussion, we have labeled these processes as Identification of Information, Advanced Cognition, and Medical Cognitive Action. Exploring problem solving processes with Bayesian network techniques can characterize students' dynamic learning processes quantitatively, identify differences in cognitive components at different stages of learning and better represent clinical problem solving features. We develop a hierarchical cognitive model as a cognitive assessment tool to describe the complex cognitive network relations, which can be applied to various clinical cognitive situations. The study concludes that the cognitive model was useful in identifying students' learning trajectories by representing the different cognitive features.